Exploring spatial heterogeneity of Antarctic sea ice algae using an autonomous underwater vehicle mounted irradiance sensor

• Published in: Frontiers in Earth Science
• Main Authors: Forrest, AL, Lund-Hansen, LC, Sorrell, BK, Bowden-Floyd, I, Lucieer, V, Cossu, R, Lange, BA, Hawes, I
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Research Foundation 2019
• Subjects: ice algae; Antarctica; McMurdo; autonomous underwater vehicles; biomass; normalized difference indices; Antarctic; McMurdo Sound; Antarc*; ice core; Sea ice
• Online Access: https://eprints.utas.edu.au/30730/; https://eprints.utas.edu.au/30730/1/133809%20-%20Exploring%20spatial%20heterogeneity%20of%20Antarctic%20sea%20ice%20algae%20using%20an%20autonomous.pdf

Sea ice algae represent a key energy source for many organisms in polar food webs, butestimating their biomass at ecologically appropriate spatiotemporal scales remains achallenge. Attempts to extend ice-core derived biomass to broader scales using remotesensing approaches has largely focused on the use of under-ice spectral irradiance.Normalized difference index (NDI) based algorithms that relate the attenuation ofirradiance by the snow-ice-algal ensemble at specific wavelengths to biomass havebeen used to explain up to 79% of the biomass of algae in limited areas. Application ofthese algorithms to datasets collected using tethered remotely operated vehicles (ROVs)has begun, generating methods for spatial sampling at scales and spatial resolutionnot achievable with ice-core sampling. Successful integration of radiometers withuntethered autonomous underwater vehicles (AUVs) offers even greater capability tosurvey broader regions to explore the spatial heterogeneity of sea ice algal communities.This work describes the pilot use of an AUV fitted with a multispectral irradiance sensorto estimate ice-algal biomass along transects beneath land-fast sea ice (~2 m thick withminimal snow cover) in McMurdo Sound, Antarctica. The AUV obtained continuous,repeatable, multi-band irradiance data, suitable for NDI-type approaches, over transectsof 500 m, with an instrument footprint of 4 m in diameter. Algorithms were developedusing local measurements of ice algae biomass and spectral attenuation of sea iceand were able to explain 40% of biomass variability. Relatively poor performance of thealgorithms in predicting biomass limited the confidence that could be placed in biomassestimates from AUV data. This was attributed to the larger footprint size of the opticalsensors integrating small-scale biomass variability more effectively than the ice core inthe platelet-dominated ice algal habitat. Our results support continued development ofremote-sensing of sea ice algal biomass at m–km spatial scales using optical methods,but caution that footprint sizes of calibration data (e.g., coring) must be compatible withoptical sensors used. AUVs offer autonomous survey techniques that could be appliedto better understand the horizontal variability of sea ice algae from nearshore ice out tothe marginal ice zone.